Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating Medicines Partnership® Schizophrenia Program
作者:Tashrif Billah, Kang Ik K. Cho, Owen Borders, Yoonho Chung, Michaela Ennis, Grace R. Jacobs, Einat Liebenthal, Daniel H. Mathalon, Dheshan Mohandass, Spero Nicholas, Ofer Pasternak, Nora Penzel, Habiballah Rahimi-Eichi, Phillip Wolff, Alan Anticevic, Kristen Laulette, Ángela Núñez, Zailyn Tamayo, Kate Buccilli, Beau‐Luke Colton, Dominic Dwyer, Larry D. Hendricks, Hok Pan Yuen, Jessica Spark, Sophie Tod, Holly Carrington, Justine Chen, Michael J. Coleman, Cheryl M. Corcoran, Anastasia Haidar, Omar John, Sinéad Kelly, Patricia Marcy, Priya Matneja, Alessia McGowan, Susan Ray, Simone Veale, Inge Winter-van Rossum, Jean Addington, Kelly Allott, Monica E. Calkins, Scott R. Clark, Ruben C. Gur, Michael P. Harms, Diana O. Perkins, Kosha Ruparel, William S. Stone, John Torous, Alison R. Yung, Eirini Zoupou, Paolo Fusar‐Poli, Vijay A. Mittal, Jai Shah, Daniel H. Wolf, Guillermo Cecchi, Tina Kapur, Marek Kubicki, Kathryn E. Lewandowski, Carrie E. Bearden, Patrick D. McGorry, René S. Kahn, John M. Kane, Barnaby Nelson, Scott W. Woods, Martha E. Shenton, the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ), Justin T. Baker, Sylvain Bouix · 发表于:Schizophrenia · 年份:2025 · DOI:10.1038/s41537-025-00560-x · 被引用次数:8 · 研究领域:Scientific Computing and Data Management、Research Data Management Practices、Cell Image Analysis Techniques
Modern research management, particularly for publicly funded studies, assumes a data governance model in which grantees are considered stewards rather than owners of important data sets. Thus, there is an expectation that collected data are shared as widely as possible with the general research community. This presents problems in complex studies that involve sensitive health information. The latter requires balancing participant privacy with the needs of the research community. Here, we report on the data operation ecosystem crafted for the Accelerating Medicines Partnership® Schizophrenia project, an international observational study of young individuals at clinical high risk for developing a psychotic disorder. We review data capture systems, data dictionaries, organization principles, data flow, security, quality control protocols, data visualization, monitoring, and dissemination through the NIMH Data Archive platform. We focus on the interconnectedness of these steps, where our goal is to design a seamless data flow and an alignment with the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles while balancing local regulatory and ethical considerations. This process-oriented approach leverages automated pipelines for data flow to enhance data quality, speed, and collaboration, underscoring the project's contribution to advancing research practices involving multisite studies of sensitive mental health conditions. An important feature is the da...